Data Science Stack Exchange
Data Science Stack Exchange

Questions tagged [sequence]

115 questions
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2 answers

How to implement "one-to-many" and "many-to-many" sequence prediction in Keras?

I struggle to interpret the Keras coding difference for one-to-many (e. g. classification of single images) and many-to-many (e. g. classification of image sequences) sequence labeling. I frequently see two different kind of codes: Type 1 is where…
Hendrik
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what is the first input to the decoder in a transformer model?

The image is from url: Jay Alammar on transformers K_encdec and V_encdec are calculated in a matrix multiplication with the encoder outputs and sent to the encoder-decoder attention layer of each decoder layer in the decoder. The previous output is…
mLstudent33
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10
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2 answers

Classification of vector sequences

My dataset is comprised of vector sequences. Each vector has 50 real-valued dimensions. The number of vectors in a sequence range from 3-5 to 10-15. In other words, the length of a sequence is not fixed. Some fair amount of the sequences (not…
Vladislavs Dovgalecs
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8
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3 answers

Algorithm for segmentation of sequence data

I have a large sequence of vectors of length N. I need some unsupervised learning algorithm to divide these vectors into M segments. For example: K-means is not suitable, because it puts similar elements from different locations into a single…
generall
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6
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2 answers

Sequence data vs time series data

What is the difference between sequence data and time series data? My understanding is that sequence data is any data where the order matters and time series is a special type of sequence data ordered by the time stamps. Is this correct? Is there a…
user2840286
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Predict a sequence given many sequences

I'm trying to find an algorithm that would fit this use case: My data: a bunch of fixed-size integer arrays, e.g. [0,2,3,4,5] [1,2,3,1,5] [4,1,2,4,5] ... Input: an array of integers, and output: prediction for the rest of the array, e.g. [0,1] ->…
Andrew Furman
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1 answer

Why do position embeddings work?

In the papers "Convolutional Sequence to Sequence Learning" and "Attention Is All You Need", positions embeddings are simply added to the input words embeddings to give the model a sense of the order of the input sequence. These position embeddings…
Robin
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5
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Classification of DNA Sequences

I have a database of 3190 instances of DNA consisting of 60 sequential DNA nucleotide positions classified according to 3 types: EI, IE, Other. I want to formulate a supervised classifier. My present approach is to formulate a 2nd order Markov…
akellyirl
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4
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In sequence models, is it possible to have training batches with different timesteps each to reduce the required padding per input sequence?

I want to train an LSTM model with variable length inputs. Specifically I want to use as little padding as possible while still using minibatches. As far as I understand each batch requires a fixed number of timesteps for all inputs, necessitating…
Tonnz
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2 answers

Can bidirectional RNN use variable sequence length?

A bidirectional RNN consists of two RNNs, one for the forward and another for the backward sequential directions, which outcome is concatenated at each time step. Would this configuration restrict the model to always use a fixed sequence length? Or…
DiMorten - Jorge Chamorro
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1 answer

Best HMM Package

What is the best HMM (Hidden Markov Model) library available in Python? I have already looked into seqlearn and hmmlearn, but both of them don't seem to be actively maintained. Thanks in advance!
Edamame
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4
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Is this a problem for a Seq2Seq model?

I'm struggling to find a tutorial/example which covers using an seq2seq model for sequential inputs other then text/translation. I have a multivariate dataset with n number of input variables each composed of sequences, and a single output sequence…
Ellio
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4
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3 answers

Are there cyclic decision trees?

Usual decision trees are directed acyclic graphs. Are there generalizations of decision trees that contain cycles analogously to recurrent neural networks? If such trees exist, can they be applied to sequences of variable length? I could not find…
Vladislav Gladkikh
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4
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Viterbi-like algorithm suggesting top-N probable state sequences implementation

Traditional Viterbi algorithm (say, for hidden Markov models) provides the most probable hidden state sequence given a sequence of observations. There probably is an algorithm for decoding top-N probable hidden states sequences (k-shortest paths or…
Anton
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Recommender Model for Human Action in Income Protection

Problem Domain I'm working on a project that involves building a model to provide recommendations on the next best step for Human supervisors to take on income protection claims. Income protection is an area of insurance that involves providing the…
Doogyb
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